The environment plays a critical role in the development, dissemination, and transmission of antimicrobial resistance (AMR). Pharmaceuticals and personal care products (PPCPs) enter the environment through direct application to the environment and through anthropogenic pollution. Although there is a growing body of evidence defining minimal selective concentrations (MSCs) of antibiotics and the role antibiotics play in horizontal gene transfer (HGT), there is limited evidence on the role of non-antibiotic PPCPs. Existing data show associations with the development of resistance or effects on bacterial growth rather than calculating selective endpoints. Research has focused on laboratory-based systems rather than in situ experiments, although PPCP concentrations found throughout wastewater, natural water, and soil environments are often within the range of laboratory-derived MSCs and at concentrations shown to promote HGT. Increased selection and HGT of AMR by PPCPs will result in an increase in total AMR abundance in the environment, increasing the risk of exposure and potential transmission of environmental AMR to humans. There is some evidence to suggest that humans can acquire resistance from environmental settings, with water environments being the most frequently studied. However, because this is currently limited, we recommend that more evidence be gathered to understand the risk the environment plays in regard to human health. In addition, we recommend that future research efforts focus on MSC-based experiments for non-antibiotic PPCPS, particularly in situ, and investigate the effect of PPCP mixtures on AMR. Environ Toxicol Chem 2022;00:1-14.
Recent evidence suggests that anthropogenic activity can increase the levels of antimicrobial resistance (AMR) in the environment. Rivers and waterways are significant examples of environmental settings that have become repositories of antibiotics and antibiotic resistance genes (ARGs). Our recent study quantified drug concentrations in freshwater samples taken at a range of sites located on the Thames catchment; the highest levels of antibiotics and other drugs were recorded downstream of waste water treatment plants (WWTPs). One specific antibiotic: Trimethoprim (TMP) was shown at elevated concentrations reaching 2000ng/L at particular sites. We have also shown a correlative relationship between the residue of TMP and the prevalence of sulfonamide antibiotic resistance genes such as sul1. Despite this, there is still no evidence of a causative relationship between TMP concentrations and the prevalence of the ARGs at river sites. The aim of the current study was to conduct in-depth analysis using a combination of large metagenomic, geospatial and chemical datasets, in order to conduct a comparison between those sites with the highest TMP and lowest TMP levels across the Thames catchment. We aimed to establish the proximity of these sites to WWTPs, their population equivalence (PE) and land coverage. A secondary aim was to investigate seasonal variation in TMP and ARGs. Exploring these factors will help to decipher the clinical relevance of ARG accumulation at river sites. A significant correlation was shown between TMP levels at river sites and their distance downstream from a WWTP. Three sites located on the Rivers Cut and Ray showed significantly higher TMP concentrations in winter compared to summer. The population equivalence (PE) for sites with the highest TMP levels was significantly higher than those with the lowest levels. The land coverage of sites with the highest TMP levels was significantly more urban/suburban than sites with the lowest TMP concentrations, which were found to be significantly more arable. Five ARGs relevant to TMP and sulfonamides were identified across the Thames catchment. The most prevalent ARG was sul1, which was significantly more prevalent in winter compared to summer. By contrast sul2 was found to be significantly more prevalent in summer compared to winter at a site on the River Coln. The prevalence of the class 1 integron marker gene (inti1) did not differ significantly by season or between sites with the highest/lowest TMP levels.
BackgroundShotgun metagenomic sequencing is increasingly popular in taxonomic and resistome-profiling of polymicrobial samples due to its agnostic nature and data versatility. However, caveats include high- cost, sequencing depth/sensitivity trade-offs, and challenging bioinformatic deconvolution. Targeted PCR-based profiling optimises sensitivity and cost-effectiveness, but can only identify prespecified targets and may introduce amplification biases. Ultra-high multiplexed PCR is a potential compromise. As no comprehensive comparative evaluation exists, we evaluated performance of each method in taxonomic/resistome-profiling of a well-defined DNA mock sample and seven “real- world” wastewater samples.ResultsWe tested three sequencing approaches (short-read shotgun metagenomics, Illumina Ampliseq™ ultra-plexed AMR Research Panel, 16S rRNA gene sequencing) with seven bioinformatic pipelines (ResPipe, Illumina DNA Amplicon App, One Codex Metagenomic-/Targeted Loci classification and Ampliseq™ Report, DADA2, and an in-house pipeline for AmpliSeq data [AmpliSeek]). Metagenomics outperformed 16S rRNA gene sequencing in accurately reconstituting a mock taxonomic profile and optimising the identification of diverse wastewater taxa, while 16S rRNA gene sequencing produced more even taxonomic outputs which may be quantitatively inaccurate but enhance detection of low abundance taxa. Shotgun metagenomic and AmpliSeq sequencing performed equally well in profiling AMR genes present in a mock sample, but AmpliSeq identified more genes in more complex, “real-world” samples, likely related to sensitivity of detection at the metagenomic sequencing depth used.ConclusionsA complementary sequencing approach employing 16S rRNA gene or shallow-metagenomic sequencing for taxonomic profiling, and the AmpliSeq AMR panel for high-resolution resistome profiling represents a potential lower-cost alternative to deep shotgun sequencing and may also be more sensitive for the detection of low-prevalence AMR genes. However, our evaluation highlights that both the sequencing and bioinformatics approach used can significantly influence results; for AmpliSeq AMR gene profiling, we developed AmpliSeek which outperformed the other pipelines tested and is open source. Sequencing approach and bioinformatic pipeline should be considered in the context of study goals and sample type, with study-specific validation when feasible.
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